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Gede Angga Pradipta, Gede Angga
Institut Teknologi Dan Bisnis STIKOM Bali
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Journal : Emerging Science Journal

 1 
Oversampling Approach Using Radius-SMOTE for Imbalance Electroencephalography Datasets Retantyo Wardoyo; I Made Agus Wirawan; I Gede Angga Pradipta
Emerging Science Journal Vol 6, No 2 (2022): April
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-02-013

Abstract

Several studies related to emotion recognition based on Electroencephalogram signals have been carried out in feature extraction, feature representation, and classification. However, emotion recognition is strongly influenced by the distribution or balance of Electroencephalogram data. On the other hand, the limited data obtained significantly affects the imbalance condition of the resulting Electroencephalogram signal data. It has an impact on the low accuracy of emotion recognition. Therefore, based on these problems, the contribution of this research is to propose the Radius SMOTE method to overcome the imbalance of the DEAP dataset in the emotion recognition process. In addition to the EEG data oversampling process, there are several vital processes in emotion recognition based on EEG signals, including the feature extraction process and the emotion classification process. This study uses the Differential Entropy (DE) method in the EEG feature extraction process. The classification process in this study compares two classification methods, namely the Decision Tree method and the Convolutional Neural Network method. Based on the classification process using the Decision Tree method, the application of oversampling with the Radius SMOTE method resulted in the accuracy of recognizing arousal and valence emotions of 78.78% and 75.14%, respectively. Meanwhile, the Convolutional Neural Network method can accurately identify the arousal and valence emotions of 82.10% and 78.99%, respectively. Doi: 10.28991/ESJ-2022-06-02-013 Full Text: PDF
IRS-BAG-Integrated Radius-SMOTE Algorithm with Bagging Ensemble Learning Model for Imbalanced Data Set Classification Lilis Yuningsih; Gede Angga Pradipta; Dadang Hermawan; Putu Desiana Wulaning Ayu; Dandy Pramana Hostiadi; Roy Rudolf Huizen
Emerging Science Journal Vol 7, No 5 (2023): October
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-07-05-04

Abstract

Imbalanced learning problems are a challenge faced by classifiers when data samples have an unbalanced distribution among classes. The Synthetic Minority Over-Sampling Technique (SMOTE) is one of the most well-known data pre-processing methods. Problems that arise when oversampling with SMOTE are the phenomenon of noise, small disjunct samples, and overfitting due to a high imbalance ratio in a dataset. A high level of imbalance ratio and low variance conditions cause the results of synthetic data generation to be collected in narrow areas and conflicting regions among classes and make them susceptible to overfitting during the learning process by machine learning methods. Therefore, this research proposes a combination between Radius-SMOTE and Bagging Algorithm called the IRS-BAG Model. For each sub-sample generated by bootstrapping, oversampling was done using Radius SMOTE. Oversampling on the sub-sample was likely to overcome overfitting problems that might occur. Experiments were carried out by comparing the performance of the IRS-BAG model with various previous oversampling methods using the imbalanced public dataset. The experiment results using three different classifiers proved that all classifiers had gained a notable improvement when combined with the proposed IRS-BAG model compared with the previous state-of-the-art oversampling methods. Doi: 10.28991/ESJ-2023-07-05-04 Full Text: PDF
Co-Authors Abdul Wahab Aditya Naray Artamerta Ayu, Desiana Wulaning Dadang Hermawan Dadang Hermawan Dandy Pramana Hostiadi Dandy Pramana Hostiadi Dandy Pramana Hostiadi I Gede Edy Artana I Gusti Ngurah Putu Arya Wijaya I Kadek Agus Ari Setiawan I Komang Agus Ady Aryanto I Made Darma Susila I Made Darma Susila, I Made I Made Darma Susila, I Made Darma Kadek Eka Sapta W Lilis Yuningsih Luh Ayu Martini M.Cs S.Kom I Made Agus Wirawan . Made Liandana Made Liandana, Made Mahendra, Tubagus Muhamad Rihamzah Muhammad Riza Hilmi Ni Luh Putri Srinadi Pande Putu Gede Putra Pertama Purnama, I Gusti Agung Vony Putu Desiana Wulaning Ayu Putu Desiana Wulaning Ayu Putu Desiana Wulaning Ayu Putu Desiana Wulaning Ayu Putu Sumardika Eka Putra Retantyo Wardoyo Rihamzah, Muhamad Roy Rudolf Huizen Tubagus Mahendra Kusuma Wiguna, I Wayan Adi Artha Wulaning Ayu, Putu Desiana Wulaning Ayu, Putu Desiana Yoga, I Gede Dian Permana Yohanes Priyo Atmojo Yohanes Priyo Atmojo Yohanes Priyo Atmojo, Yohanes